Ejtm3 experiences after ChatGPT and other AI approaches: values, risks, countermeasures.

Area of Science:

• Artificial Intelligence
• Machine Learning
• Robotics

Background:

• Artificial Intelligence (AI) is a rapidly evolving technology with the potential to revolutionize scientific research.
• AI can generate data and insights without direct laboratory experimentation, raising concerns about plagiarism and data integrity.
• The increasing sophistication of AI necessitates new methods for editors and referees to evaluate scientific submissions.

Purpose of the Study:

• To explore the challenges editors and referees face in identifying AI-generated content in scientific publications.
• To propose strategies for rigorous evaluation of author track records and research methodologies.
• To establish guidelines for the transparent declaration of AI usage in scientific manuscripts.

Main Methods:

• Review of current AI capabilities in data generation and knowledge synthesis.
• Analysis of case studies involving AI-generated content in scientific journals.
• Development of a framework for editors and referees to assess the authenticity of research findings.
• Proposal for mandatory disclosure of AI tools and their applications in manuscript submissions.

Main Results:

• AI can generate plausible-sounding scientific data, making it difficult to distinguish from human-generated research.
• Rigorous evaluation of author history and established research practices are crucial for detecting AI-generated content.
• Mandatory declaration of AI use, including the type and purpose, can enhance transparency and accountability.
• The proposed framework aims to mitigate risks of plagiarism and establish clear liabilities.

Conclusions:

• Editors and referees must adapt their evaluation processes to address the challenges posed by AI in scientific publishing.
• Transparency in AI usage through mandatory declarations is essential for maintaining scientific integrity.
• While AI is not banned, its responsible use and clear disclosure are paramount for future research.
• The study emphasizes the need for a collaborative approach between researchers, editors, and AI developers to ensure ethical AI integration.